Ask HN: Is PhD the only way to be able to enter research?
19 comments
From what I understand, you don't need a PhD to contribute to research and be impactful, depending on the subject. However, most people that do end up having one. I know a few people whose hobby is independent research and they don't have PhD's and yet their work is very interesting and could one day make an impact.
For example, there's Ben from Lunar Homestead (https://lunarhomestead.com/) who presented his work (SPORE) at the Moon Society's last conference. He's done quite a job at educating himself and you wouldn't know he wasn't certified unless he told you. He's proud of it though and tends to tell people that education and contribution to science is something you can achieve if you put your mind to it.
If you want to be in a research position alone, I don't know what to say. There's jobs around that let you work closely with researchers as an engineer. I've been seeing a lot of those around lately here in Iowa, especially concerning crops.
Otherwise, the alternative is to monetize your research but then you'll be doing a LOT more than research. Research would probably be 10% after all is said and done.
For example, there's Ben from Lunar Homestead (https://lunarhomestead.com/) who presented his work (SPORE) at the Moon Society's last conference. He's done quite a job at educating himself and you wouldn't know he wasn't certified unless he told you. He's proud of it though and tends to tell people that education and contribution to science is something you can achieve if you put your mind to it.
If you want to be in a research position alone, I don't know what to say. There's jobs around that let you work closely with researchers as an engineer. I've been seeing a lot of those around lately here in Iowa, especially concerning crops.
Otherwise, the alternative is to monetize your research but then you'll be doing a LOT more than research. Research would probably be 10% after all is said and done.
A PhD is usually where you learn what research _is_ and how it is done, that's the reason why it is usually a 'minimum requirement'
If you plan to spend some years in reading and implementing papers to become a researcher anyway.. You can probably go back to school and get a PhD, this will be way more efficient than randomly reading without guidance.
Furthermore, a researcher do not spend his days to implement state of the art algorithms, he tries to push science a little further in very small steps, implementing is just part of the process.
Even when you have a PhD, pure research jobs are pretty rare but from your description you are more looking into innovative startups that implement SoTA papers (more R&D than research), this is more common and most of the jobs in robotic require some experimental setup and "research". In those startup the PhD requirement is often flexible !
But this "research" is often very different from the research done in academy.
Try to clarify what kind of research you want to do so that people can give you more precise advices :)
If you plan to spend some years in reading and implementing papers to become a researcher anyway.. You can probably go back to school and get a PhD, this will be way more efficient than randomly reading without guidance.
Furthermore, a researcher do not spend his days to implement state of the art algorithms, he tries to push science a little further in very small steps, implementing is just part of the process.
Even when you have a PhD, pure research jobs are pretty rare but from your description you are more looking into innovative startups that implement SoTA papers (more R&D than research), this is more common and most of the jobs in robotic require some experimental setup and "research". In those startup the PhD requirement is often flexible !
But this "research" is often very different from the research done in academy.
Try to clarify what kind of research you want to do so that people can give you more precise advices :)
Thanks for the reply and the valuable feedback!
>If you plan to spend some years in reading and implementing papers to become a researcher anyway.. You can probably go back to school and get a PhD, this will be way more efficient than randomly reading without guidance.
Well the core question is just that: if my goal is to become a researcher, should I just go for a PhD, or is there another way. And also the reason I resigned from my work, to first see how far I can improve my understanding on my own (and how much that can amount to finding a research opportunity).
>Furthermore, a researcher do not spend his days to implement state of the art algorithms, he tries to push science a little further in very small steps, implementing is just part of the process.
I'm aware that implementing SoTA is not necessarily research, but still often something done by PhD while PhD to understand/test/reproduce/get insight of a certain SoTA approach, to build/modify on it.
>Even when you have a PhD, pure research jobs are pretty rare
I'm also aware of this fact, as I met plenty of PhD people at my previous start up(mostly doing the implementation I mentioned above, in their respective field of expertise), although most of them wasn't that interested in research anymore.
I use research to cover both the process of discovering new and noble things, and finding a suitable SoTA for a specific engineering problem (usually what PhD going to industry end up doing, it seems) because as I see it, it is also valuable "research" in the field of robotics. (For context, my particular interest is in Reinforcement Learning application in Robotics) Engineering application of theory in industries seems like a good "feedback" to the academic community too =)
But I'm aware that my view of things is limited/naive, and that's why I'm asking for others experience. Maybe I should've been a bit more specific, though!
>If you plan to spend some years in reading and implementing papers to become a researcher anyway.. You can probably go back to school and get a PhD, this will be way more efficient than randomly reading without guidance.
Well the core question is just that: if my goal is to become a researcher, should I just go for a PhD, or is there another way. And also the reason I resigned from my work, to first see how far I can improve my understanding on my own (and how much that can amount to finding a research opportunity).
>Furthermore, a researcher do not spend his days to implement state of the art algorithms, he tries to push science a little further in very small steps, implementing is just part of the process.
I'm aware that implementing SoTA is not necessarily research, but still often something done by PhD while PhD to understand/test/reproduce/get insight of a certain SoTA approach, to build/modify on it.
>Even when you have a PhD, pure research jobs are pretty rare
I'm also aware of this fact, as I met plenty of PhD people at my previous start up(mostly doing the implementation I mentioned above, in their respective field of expertise), although most of them wasn't that interested in research anymore.
I use research to cover both the process of discovering new and noble things, and finding a suitable SoTA for a specific engineering problem (usually what PhD going to industry end up doing, it seems) because as I see it, it is also valuable "research" in the field of robotics. (For context, my particular interest is in Reinforcement Learning application in Robotics) Engineering application of theory in industries seems like a good "feedback" to the academic community too =)
But I'm aware that my view of things is limited/naive, and that's why I'm asking for others experience. Maybe I should've been a bit more specific, though!
RL is extensively used in robotics ;)
If you want to go for a PhD, I suggest reading Sutton's book on RL (at least the important parts for what you want to do), followed by recent RL papers and RL papers in robotics that pick your interest, understand them fully. Aim for journal papers and major conferences only (high impact factor is a first metric that comes to mind).
The main bit is to try to formulate an important research question you're interested in which is not already explored in the vast litterature and plan which experiments you need to carry and what do you need to change if some of them fail.
If you want to engage in a PhD, an important and well studied research question will increase your chances of getting accepted in a PhD program.
The main advantage in doing a PhD in a uni is that you can share and learn knowledge from other students and advisors, as well as have insights in what are ideas worth pursuing and what are small improvement that no one care about.
At uni you usually work on the kind of research meant to improve the knowledge and less on the general engineering problems. Engineering problems are byproduct of the knowledge you are building. A lot of uni work very closely with industries in practical fields like robotics, you'll have plenty of opportunities to apply what you are building directly on engineering problems. But that will not be the main focus.
In my experience it is considered less 'valuable research' to try to apply some SoTA to a specific engineering problem in academy, and usually proposals of this kind are rejected.
Hope this is helpful :)
If you want to go for a PhD, I suggest reading Sutton's book on RL (at least the important parts for what you want to do), followed by recent RL papers and RL papers in robotics that pick your interest, understand them fully. Aim for journal papers and major conferences only (high impact factor is a first metric that comes to mind).
The main bit is to try to formulate an important research question you're interested in which is not already explored in the vast litterature and plan which experiments you need to carry and what do you need to change if some of them fail.
If you want to engage in a PhD, an important and well studied research question will increase your chances of getting accepted in a PhD program.
The main advantage in doing a PhD in a uni is that you can share and learn knowledge from other students and advisors, as well as have insights in what are ideas worth pursuing and what are small improvement that no one care about.
At uni you usually work on the kind of research meant to improve the knowledge and less on the general engineering problems. Engineering problems are byproduct of the knowledge you are building. A lot of uni work very closely with industries in practical fields like robotics, you'll have plenty of opportunities to apply what you are building directly on engineering problems. But that will not be the main focus.
In my experience it is considered less 'valuable research' to try to apply some SoTA to a specific engineering problem in academy, and usually proposals of this kind are rejected.
Hope this is helpful :)
>I suggest reading Sutton's book on RL
I've read part of the book, and followed David Silvers UCL lectures on my own, and have been focused on reading all the recent algorithm/approaches in the field last few weeks.
>RL is extensively used in robotics ;)
Is it? From Andrej Karpathy:s HN comment[1] and Alex Ipran's[2] comment in 2017 & 2018 I feel like it is just recently (around mid 2019) actual trial on robotics have started to show promise (SAC, E2E) in academia, and only a handful of start ups have approached this (Covariant, founded by one of the professor in the two papers above) But then again, I might be missing some insight here.
Thank you for the extremely valuable feedback! :) The formulation of important research question is also something I'm trying to figure out by, getting myself updated in the field to the point of understanding what is missing (or under-studied)!
As I mentioned in another comment I'm in the process of applying at a public research institute (as an research assistant) with potential for an industrial PhD position, so those feedback is just on-point valuable for me right now :)
(Although the research is not RL focused but is trying to tackle the identical problem formulation in robotics using ML/AI algorithms)
[1] https://news.ycombinator.com/item?id=13519044 [2] https://www.alexirpan.com/2018/02/14/rl-hard.html
I've read part of the book, and followed David Silvers UCL lectures on my own, and have been focused on reading all the recent algorithm/approaches in the field last few weeks.
>RL is extensively used in robotics ;)
Is it? From Andrej Karpathy:s HN comment[1] and Alex Ipran's[2] comment in 2017 & 2018 I feel like it is just recently (around mid 2019) actual trial on robotics have started to show promise (SAC, E2E) in academia, and only a handful of start ups have approached this (Covariant, founded by one of the professor in the two papers above) But then again, I might be missing some insight here.
Thank you for the extremely valuable feedback! :) The formulation of important research question is also something I'm trying to figure out by, getting myself updated in the field to the point of understanding what is missing (or under-studied)!
As I mentioned in another comment I'm in the process of applying at a public research institute (as an research assistant) with potential for an industrial PhD position, so those feedback is just on-point valuable for me right now :)
(Although the research is not RL focused but is trying to tackle the identical problem formulation in robotics using ML/AI algorithms)
[1] https://news.ycombinator.com/item?id=13519044 [2] https://www.alexirpan.com/2018/02/14/rl-hard.html
> Is it?
DL/RL/etc. Are very hype right now in research, everything is moving at a very fast speed. A lot of 'RL applied to robotics' papers are accepted at top conferences (and even more rejected)
Several tools are in development to increase dramatically the speed at which research can be done ;)
A simple Google scholar search on reinforcement learning and robotics limited to 2020 only should give you lots of good results.
I wish you the best ;)
DL/RL/etc. Are very hype right now in research, everything is moving at a very fast speed. A lot of 'RL applied to robotics' papers are accepted at top conferences (and even more rejected)
Several tools are in development to increase dramatically the speed at which research can be done ;)
A simple Google scholar search on reinforcement learning and robotics limited to 2020 only should give you lots of good results.
I wish you the best ;)
I have a (research/thesis) master's in mechanical engineering and currently work as a research assistant in a university research lab that works on many topics, some of which related to robotics.
It's fun, interesting work with many upsides, like working with very smart people, flexible work week, possibility of teaching classes as a contract lecturer and making many contacts in industry, especially with R&D departments, since I work on many projects with industry funding. Not to mention, on campus daycare.
The downside is salaries don't compare to industry engineer salaries since, at the institution I work at, all RAs are unionized and on the same pay scale, no matter if your topic is law, biology, english or engineering. Moreover, it's a dead end internally: to become a PI/professor, I'd have to get a PhD and complete at least 1 postdoc, most likely in a different institution that is considered elite, and even then it's a crapshoot.
It's fun, interesting work with many upsides, like working with very smart people, flexible work week, possibility of teaching classes as a contract lecturer and making many contacts in industry, especially with R&D departments, since I work on many projects with industry funding. Not to mention, on campus daycare.
The downside is salaries don't compare to industry engineer salaries since, at the institution I work at, all RAs are unionized and on the same pay scale, no matter if your topic is law, biology, english or engineering. Moreover, it's a dead end internally: to become a PI/professor, I'd have to get a PhD and complete at least 1 postdoc, most likely in a different institution that is considered elite, and even then it's a crapshoot.
To a first approximation, yes. There are exceptions of course and people fall into them. But the energy that will go into trying to create your own exception is likely to be greater than the energy that goes into a PhD and the odds of winding up in a research position are lower than with a PhD.
Think about it from the perspective of a person hiring for a research position. How would not having a PhD be a positive? Not having a PhD doesn't correlate with anything positive. It correlates with less training, less commitment, and less experience. And it correlates with the candidate not valuing these things.
The PhD is more in your control than finding a research position without one. Good luck.
Think about it from the perspective of a person hiring for a research position. How would not having a PhD be a positive? Not having a PhD doesn't correlate with anything positive. It correlates with less training, less commitment, and less experience. And it correlates with the candidate not valuing these things.
The PhD is more in your control than finding a research position without one. Good luck.
See if there are jobs at semi-governmental institutes. Think NOAA, NASA and the likes. These have engineering positions which require you to collaborate with scientists. The right project can earn you your name on a research paper.
I'm not in/from the US, so I can't apply for those position unfortunately, but I'm currently applying to semi-governmental institute technical-assistant position. But I'm afraid it would be a position that would be a "glorified IT-support/sysadmin" with some paper proof-reading... which is a point I'm about to ask on upcoming meeting.
As the other comment pointed out, if I have no say in direction/approach I'm skeptical how much I would enjoy working for it (with a reduced salary nonetheless)
As the other comment pointed out, if I have no say in direction/approach I'm skeptical how much I would enjoy working for it (with a reduced salary nonetheless)
I'm not in/from the US either, but almost every country has an institute dedicated to research in climate, space, defense or avionics.
It's not a bad idea to apply as a sysadmin if you can't get anything else. It'll get a foot in the door, and you'll learn how the organization is set up, what its daughter/sister organizations are, etc.
It's not a bad idea to apply as a sysadmin if you can't get anything else. It'll get a foot in the door, and you'll learn how the organization is set up, what its daughter/sister organizations are, etc.
This is a good suggestion, but it might be limited depending on what level the OP is interested in. I would expect that the OP would be able to be a part of research, but would be unlikely that they would be able to have much say in the direction.
Why not just work with people you enjoy working with on your own research independently?
If it provides someone with value, sure you can raise funds and generate revenue and dedicate your life for research. Of course it's easier said than done, but it's possible. Why not?
I believe that research-oriented tech startups can change the world and create/dominate new/emerging industries.
You'll have more skin in the game tying your research to a business, which will probably make you think bigger and change the world.
If done right (financing your research), you can have people more experienced than you are work with you, and learn from them.
If it provides someone with value, sure you can raise funds and generate revenue and dedicate your life for research. Of course it's easier said than done, but it's possible. Why not?
I believe that research-oriented tech startups can change the world and create/dominate new/emerging industries.
You'll have more skin in the game tying your research to a business, which will probably make you think bigger and change the world.
If done right (financing your research), you can have people more experienced than you are work with you, and learn from them.
The national Labs are in good place to get started in research. They have openings in all sorts of different levels. Another option is University Research spinouts. This is like galois and Grammatech. you do not need phds to work with all these places, but they do have positions that are only for phds
Wow, I didn't see any reply/upvote a couple of hours after posting so thought this would get no comments. what a pleasant surprise to wake up to!
Thank you everyone for the insightful replies!
Thank you everyone for the insightful replies!
I've been doing independent, non-funded, self-chosen research for years. The only real issue is that most of the papers of interest have been paywalled ($40 for a 4 page paper). I only have a Master's degree.
This is something I've been wondering if possible for a while too; and it is one of the reason I resigned from my previous job, to spend my full time in reading papers, reaching out to researcher, implement/test existing papers. Fortunately, the software side of robotics is still possible to test/conduct independent research with help of simulations, open source code/platforms and papers.
But I'm very new to this, so I would like to know more about your experience (limitation, downside/pros) doing this!
But I'm very new to this, so I would like to know more about your experience (limitation, downside/pros) doing this!
And such papers are not available on sci-hub?
So why not pay for it?
After working at two Startups, the latter one at hiring stage explicitly stating reading/implementing state-of-the-art methods as job description (Which I didn't end up doing), I've come to the impression that most of the time, this is not the case.
So I've been looking for institute/places that are more research focused, but almost all of them seems to put a PhD at "Minimum requirement" for application. Is there anyone out there that do more research related work, but ended up doing that without a PhD in the bag? If so, how?